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Leni Pertiwi
Universitas Budi Darma, Medan
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Other

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Penerapan Algoritma Text Mining, Steaming Dan Texrank Dalam Peringkasan Bahasa Inggris Leni Pertiwi
Bulletin of Multi-Disciplinary Science and Applied Technology Vol 1 No 3 (2022): April 2022
Publisher : Forum Kerja Sama Penddikan Tinggi (FKPT)

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Abstract

Text summarization in English is used to summarize a text using a computer to get a summary of the text. The text summarization method uses extractives because this method takes important information from a text without changing it or the information. One of the algorithms that can be used to summarize text in English is by using the TextRank algorithm. The advantage of the TextRank algorithm is that it does not require in-depth knowledge of a language and does not require training data to be able to summarize text. The way this algorithm works is to represent sentences in the text into a graph, calculating the value of each sentence using questions (similarities) between sentences to determine the summary results. In addition to using similarity to determine important sentences, this study also uses a modified TextRank, namely by using levenshtein distance to calculate summaries by comparing the similarities between strings by entering, entering, or replacing character strings. Summarization of text in English using TextRank is done by summarizing 100 English texts which will then be evaluated using ROUGE. ROUGE evaluation works by comparing the summary results from TextRank with manual summaries by experts in the field of English. To facilitate the ranking requires a text mining algorithm, using text mining algorithms can be used to get actual results.
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